This README introduces the Simplex Method, a popular algorithm for solving linear programming problems in R. Linear programming optimizes an objective function, such as maximizing or minimizing a ...

The dual simplex method is a variation of the simplex method that can be used to solve linear programming problems when the initial solution is infeasible.

This repository contains a Python implementation of the Simplex algorithm for solving Linear Programming Problems (LPPs). The Simplex algorithm is an iterative method that optimizes a linear objective ...

Learn how to use linear programming models to optimize complex industrial engineering systems and processes, such as production planning, resource allocation, scheduling, transportation, and ...

Abstract A new variant of the Adaptive Method (AM) of Gabasov is presented, to minimize the computation time. Unlike the original method and its some variants, we need not to compute the inverse of ...

Moreover, a new, ratio-test-free pivoting rule is proposed, significantly reducing computational cost at each iteration. Our numerical experiments show that the method is very promising, at least for ...

Linear programming is the most fundamental optimization problem with applications in many areas including engineering, management, and economics. The simplex method is a practical and efficient ...

The aim of this paper is to introduce a formulation of linear programming problems involving intuitionistic fuzzy variables. Here, we will focus on duality and a simplex-based algorithm for these ...

This study proposes a novel technique for solving linear programming problems in a fully fuzzy environment. A modified version of the well-known dual simplex method is used for solving fuzzy linear ...